Intelligent harvesting robot path control method considering time delay and environmental constraints

Abstract

The invention discloses an intelligent harvesting robot path control method considering time delay and environmental constraints, and belongs to the technical field of unmanned auxiliary driving in modern agriculture. The method comprises the following steps: establishing a kinetic model, a kinematic model and a harvester-ground stress model of a harvester steering system, constructing a control system model considering input delay and external disturbance, and taking a comprehensive error as a state variable; constraining the state variable based on a preset performance function, and converting a constrained variable into an unconstrained variable through an error conversion function; aiming at two conditions of steady input time delay and time-varying input time delay, respectively constructing saturation compensation variables based on steady time delay and time-varying time delay estimation values, and designing corresponding control input based on a backstepping method and a Lyapunov stability theorem. According to the method, tracking errors can be effectively restrained, the influence of input time delay on a tracking system is compensated, and the automatic driving navigation effect of the harvester is improved.

Description

technical field [0001] The invention belongs to the technical field of unmanned assisted driving in modern agriculture, and in particular relates to a path control method for an intelligent harvesting robot considering time delay and environmental constraints. Background technique [0002] The auxiliary driving system of the harvester is affected by the transmission of control signals and the action execution of the steering mechanism, which will produce a time lag phenomenon, which will reduce the stability and dynamic performance of the control system, affect the control accuracy and work efficiency of the auxiliary driving system of the harvester, and limit the agricultural production efficiency. Harvester damage. At present, the tracking control methods for harvesters mainly include PID control, pure tracking control, fuzzy control, model predictive control, etc., or optimize parameters and enhance robustness through the joint design of two or more methods. The previous...

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Problems solved by technology

The previous algorithms did not consider the influence of time lag on the path tracking control system, while the model predictive control has a predictive function, that is, it can predict the future control input in advance according to the current control input of the system and past historical information. Compensate for the lag of the harvester to a certain extent, but the computational cost required to calculate the optimal value is relatively high

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